我正在运行 python 3.11 和带有 gguf 模型的最新版本的 llama-cpp-python
我希望代码像聊天机器人一样正常运行,但我收到了这个错误:
Traceback (most recent call last):
File "d:\AI Custom\AI Arush\server.py", line 223, in <module>
init()
File "d:\AI Custom\AI Arush\server.py", line 57, in init
m_eval(model, m_tokenize(model, PROMPT_INIT, True), False, "Starting up...")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "d:\AI Custom\AI Arush\server.py", line 182, in m_tokenize
n_tokens = llama_cpp.llama_tokenize(
^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: llama_tokenize() missing 2 required positional arguments: 'add_bos' and 'special'
这是我的标记化代码:
def m_tokenize(model: llama_cpp.Llama, text: bytes, add_bos=False, special=False):
assert model.ctx is not None
n_ctx = llama_cpp.llama_n_ctx(model.ctx)
tokens = (llama_cpp.llama_token * int(n_ctx))()
n_tokens = llama_cpp.llama_tokenize(
model.ctx,
text,
tokens,
n_ctx,
llama_cpp.c_bool(add_bos),
)
if int(n_tokens) < 0:
raise RuntimeError(f'Failed to tokenize: text="{text}" n_tokens={n_tokens}')
return list(tokens[:n_tokens])
请帮忙...谢谢
TypeError: llama_tokenize() missing 2 required positional arguments: 'add_bos' and 'special'
要解决该错误,您需要将参数
add_bos
和 special
包含到 llama_tokenize()
函数中...
def m_tokenize(model: llama_cpp.Llama, text: bytes, add_bos=False, special=False):
assert model.ctx is not None
n_ctx = llama_cpp.llama_n_ctx(model.ctx)
tokens = (llama_cpp.llama_token * int(n_ctx))()
# Include the missing arguments in the function call
n_tokens = llama_cpp.llama_tokenize(
model.ctx,
text,
tokens,
n_ctx,
# You should check if llama_cpp.c_bool(add_bos) is returning a c_boo value also you have the arguments add_bos=False and special=False in this function
llama_cpp.c_bool(add_bos),
# You should check if llama_cpp.c_bool(special) is returning a c_boo value
llama_cpp.c_bool(special) # Include the special argument
)
if int(n_tokens) < 0:
raise RuntimeError(f'Failed to tokenize: text="{text}" n_tokens={n_tokens}')
return list(tokens[:n_tokens])
来自 llama_cpp.py (GitHub),代码行从 1817 开始
def llama_tokenize(
model: llama_model_p,
text: bytes,
text_len: Union[c_int, int],
tokens, # type: Array[llama_token]
n_max_tokens: Union[c_int, int],
add_bos: Union[c_bool, bool],
special: Union[c_bool, bool],
) -> int:
"""Convert the provided text into tokens."""
return _lib.llama_tokenize(
model, text, text_len, tokens, n_max_tokens, add_bos, special
)
_lib.llama_tokenize.argtypes = [
llama_model_p,
c_char_p,
c_int32,
llama_token_p,
c_int32,
c_bool,
c_bool,
]
_lib.llama_tokenize.restype = c_int32